2023

• Robust and Tiny Binary Neural Networks using Gradient-based Explainability Methods.
  Muhammad Sabih, Mikail Yayla, Frank Hannig, Jürgen Teich, Jian-Jia Chen
  EuroMLSys'23 (accepted for publication)
• HW/SW Codesign for Approximation-Aware Binary Neural Networks.
  Abhilasha Dave, Fabio Frustaci, Fanny Spagnolo, Mikail Yayla, Jian-Jia Chen, Hussam Amrouch
  IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS)
• Robust and Efficient Machine Learning for Emerging Resource-Constrained Embedded Systems (abstract, poster)
  Mikail Yayla, Hussam Amrouch, Jian-Jia Chen
  Poster Presentation for PhD Forum (DATE'23 and VTS'23)
• Global by Local Thresholding in Binarized Neural Networks for Efficient Crossbar Accelerator Design.
  Mikail Yayla, Fabio Frustaci, Fanny Spagnolo, Jian-Jia Chen, Hussam Amrouch
  (under review)
• HEP-BNN: A Framework for Finding Low-Latency Execution Configurations of BNNs on Heterogenerous Multiprocesser Platforms.
  Leonard David Bereholschi, Ching-Chi Lin, Mikail Yayla, Jian-Jia Chen
  AccML@HiPEAC'23: 5th Workshop on Accelerated Machine Learning

2022

• TREAM: A Tool for Evaluating Error Resilience of Tree-based Models using Approximate Memory.
  Mikail Yayla, Zahra Valipour Dehnoo, Mojtaba Masoudinejad, and Jian-Jia Chen
  SAMOS XXII International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation
• Memory-Efficient Training of Binarized Neural Networks on the Edge.
  Mikail Yayla and Jian-Jia Chen
  Design Automation Conference (DAC'22)
• Reliable Binarized Neural Networks on Unreliable Beyond von-Neumann Architecture.
  Mikail Yayla, Simon Thomann, Sebastian Buschjäger, Katharina Morik, Jian-Jia Chen, and Hussam Amrouch
  IEEE Transactions on Curcuits and Systems I (TCAS-I)
• Deep Learning Based Driver Model and Fault Detection for Automated Racecar System Testing.
  Yousef Abdulhamed, Christoph Schaefer, Mikail Yayla, Ching-Chi Lin, Jian-Jia Chen
  European Automotive Reliability, Test and Safety (eARTS), DATE'22 Workshop

2021

• FeFET-based Binarized Neural Networks Under Temperature-dependent Bit Errors.
  Mikail Yayla, Sebastian Buschjäger, Aniket Gupta, Jian-Jia Chen, Jörg Henkel, Katharina Morik, Kuan-Hsun Chen, Hussam Amrouch.
  IEEE Transactions on Computers (TC)
• Binarized SNNs: Efficient and Error-Resilient Spiking Neural Networks through Binarization.
  Ming-Liang Wei, Mikail Yayla, Shu-Yin Ho, Jian-Jia Chen, Chia-Lin Yang, Hussam Amrouch.
  International Conference On Computer Aided Design (ICCAD'21)
• Universal Approximation Theorems for Fully Connected Binarized Neural Networks.
  Mikail Yayla, Mario Günzel, Burim Ramosaj, Jian-Jia Chen.
  CoRR abs/2102.02631
• Bit Error Tolerance Metrics for Binarized Neural Networks.
  Sebastian Buschjäger, Jian-Jia Chen, Kuan-Hsun Chen, Mario Günzel, Christian Hakert, Katharina Morik, Rodion Novkin, Lukas Pfahler and Mikail Yayla.
  SLOHA (DATE'21 Workshop)
• FeFET and NCFET for Future Neural Networks: Visions and Opportunities.
  Mikail Yayla, Kuan-Hsun Chen, Georgios Zervakis, Jörg Henkel, Jian-Jia Chen and Hussam Amrouch.
  In Design, Automation and Test in Europe Conference (DATE'21), Special Session
• Margin-Maximization in Binarized Neural Networks for Optimizing Bit Error Tolerance.
  Sebastian Buschjäger, Jian-Jia Chen, Kuan-Hsun Chen, Mario Günzel, Christian Hakert, Katharina Morik, Rodion Novkin, Lukas Pfahler and Mikail Yayla.
  In Design, Automation and Test in Europe Conference (DATE'21), Best Paper Candidate

2020

• Software-Based Memory Analysis Environments for In-Memory Wear-Leveling.
  Christian Hakert, Kuan-Hsun Chen, Mikail Yayla, Georg von der Brüggen, Sebastian Bloemeke and Jian-Jia Chen.
  In 25th Asia and South Pacific Design Automation Conference ASP-DAC 2020, Invited Paper
• Towards Explainable Bit Error Tolerance of Resistive RAM-Based Binarized Neural Networks.
  Sebastian Buschjäger, Jian-Jia Chen, Kuan-Hsun Chen, Mario Günzel, Christian Hakert, Katharina Morik, Rodion Novkin, Lukas Pfahler and Mikail Yayla.
  CoRR abs/2002.00909

2019

• Stack Usage Analysis for Efficient Wear Leveling in Non-Volatile Main Memory Systems.
  Christian Hakert, Mikail Yayla, Kuan-Hsun Chen, Georg von der Brüggen, Jian-Jia Chen, Sebastian Buschjäger, Katharina Morik, Paul R. Genssler, Lars Bauer, Hussam Amrouch and Jörg Henkel.
  In 1st ACM/IEEE Workshop on Machine Learning for CAD (MLCAD)
• Nanoparticle Classification Using Frequency Domain Analysis on Resource-Limited Platforms.
  Mikail Yayla, Anas Toma, Kuan-Hsun Chen, Lenssen, Victoria Shpacovitch, Roland Hergenröder, Frank Weichert and Jian-Jia Chen.
  Journal of Sensors 19 4318
• Resource-Efficient Nanoparticle Classification Using Frequency Domain Analysis.
  Mikail Yayla, Anas Toma, Jan Eric Lenssen, Victoria Shpacovitch, Kuan-Hsun Chen, Frank Weichert and Jian-Jia Chen.
  In BVM'19 Workshop

2018

• Fault Tolerance on Control Applications: Empirical Investigations of Impacts from Incorrect Calculations.
  Mikail Yayla, Kuan-Hsun Chen and Jian-Jia Chen.
  In 4th Workshop on Emerging Ideas and Trends in Engineering of Cyber-Physical Systems (EITEC'18@CPSWEEK)